Instructions to use HanzoHuang/YOLOv10-RKNN2-Ultralytics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use HanzoHuang/YOLOv10-RKNN2-Ultralytics with YOLOv10:
from huggingface_hub import hf_hub_download from ultralytics import YOLOv10 # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("HanzoHuang/YOLOv10-RKNN2-Ultralytics", "<weights>.pt") model = YOLOv10(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download source/environment.json from HanzoHuang/YOLOv10-RKNN2-Ultralytics: direct link, hf CLI and curl.
- Browser
- Download file 344 Bytes
-
https://huggingface.co/HanzoHuang/YOLOv10-RKNN2-Ultralytics/resolve/main/source/environment.json
- Command line
-
hf download hf://HanzoHuang/YOLOv10-RKNN2-Ultralytics/source/environment.json
-
curl -L -o environment.json https://huggingface.co/HanzoHuang/YOLOv10-RKNN2-Ultralytics/resolve/main/source/environment.json
344 Bytes
| { | |
| "python": "3.11.15", | |
| "platform": "Linux-6.8.0-124-generic-x86_64-with-glibc2.39", | |
| "ultralytics": "8.4.184", | |
| "rknn_toolkit2": "2.3.2", | |
| "tools": { | |
| "convert-model.py": "43a013afc01235c14ffc630faa983461777c1d1a2ca5e77c47e906d7dca54847", | |
| "rknn_export.py": "34b3c38badc7f9872b1ea1adbdd6e01b8f647a56157d7c69fe9578a553042af9" | |
| } | |
| } | |